By Ling Shao, Jungong Han, Pushmeet Kohli, Zhengyou Zhang
This publication offers an interdisciplinary choice of state-of-the-art learn on RGB-D dependent machine imaginative and prescient. positive factors: discusses the calibration of colour and intensity cameras, the relief of noise on intensity maps and strategies for taking pictures human functionality in 3D; studies a variety of purposes which use RGB-D info to reconstruct human figures, evaluation strength intake and acquire exact motion type; provides an process for 3D item retrieval and for the reconstruction of fuel circulate from a number of Kinect cameras; describes an RGB-D computing device imaginative and prescient method designed to help the visually impaired and one other for smart-environment sensing to help aged and disabled humans; examines the powerful positive factors that signify static hand poses and introduces a unified framework to implement either temporal and spatial constraints for hand parsing; proposes a brand new classifier structure for real-time hand pose attractiveness and a singular hand segmentation and gesture acceptance system.
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Extra info for Computer Vision and Machine Learning with RGB-D Sensors
Commonwealth of Australia, pp 77–86 16. Huynh T, Min R, Dugelay J-L (2013) An efficient LBP-based descriptor for facial depth images applied to gender recognition using RGB-D face data. In: Computer vision-ACCV 2012 workshops. Springer, pp 133–145 17. Izadi S, Newcombe R, Kim D, Hilliges O, Molyneaux D, Hodges S, Kohli P, Shotton J, Davison A, Fitzgibbon A (2011) Kinectfusion: real-time dynamic 3D surface reconstruction and interaction. In: ACM SIGGRAPH 2011 talks. ACM, p 23 18. Janoch A, Karayev S, Jia Y, Barron JT, Fritz M, Saenko K, Darrell T (2013) A category-level 3D object dataset: putting the kinect to work.
2 Photometric Approaches In addition to the depth sensor based on geometric approach, photometric cues play an important role in estimating the 3D information. The intuition here is that the object appearance viewed from a fixed position will be different, depending on the various lighting conditions. For example, given a white sphere illuminated by a point source which is far away, the surface points whose normal orientations have smaller angles with the lighting direction look brighter and vice versa.
As shown in Fig. 21, the GelSight camera demonstrates a depth resolution of 2 microns, which is superior to geometric-based approaches (and of course Kinectstyle cameras). 17 Mobile 3D Cameras As the cost and size of mobile cameras and 3D sensors continue to decrease, consumer electronic manufacturers are finding it increasingly more feasible to incorporate 3D cameras into the next generation of mobile devices. In particular, industry trends show an intensified focus on applications within the context of augmented reality, image refocusing, and real-time key point tracking.